Tree Diameter, Tree Width, Stem Diameter, Diameter at Breast Height, DBH

Chapter Contents (Back)
Biomass Measurement. Tree. Stem Diameter. Tree Stem. Tree Diameter. Diameter at Breast Height.
See also Biomass Measurements for Individual Trees.
See also Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS.

Lovell, J.L., Jupp, D.L.B., Newnham, G.J., Culvenor, D.S.,
Measuring tree stem diameters using intensity profiles from ground-based scanning lidar from a fixed viewpoint,
PandRS(66), No. 1, January 2011, pp. 46-55.
Elsevier DOI 1101
LIDAR; Forestry; Inventory; Laser scanning; Terrestrial BibRef

Ringdahl, O.[Ola], Hohnloser, P.[Peter], Hellström, T.[Thomas], Holmgren, J.[Johan], Lindroos, O.[Ola],
Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner,
RS(5), No. 10, 2013, pp. 4839-4856.
DOI Link 1311

Saremi, H.[Hanieh], Kumar, L.[Lalit], Stone, C.[Christine], Melville, G.[Gavin], Turner, R.[Russell],
Sub-Compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus radiata D. Don Plantation Examined Using Airborne LiDAR Data,
RS(6), No. 8, 2014, pp. 7592-7609.
DOI Link 1410

Kankare, V.[Ville], Liang, X.L.[Xin-Lian], Vastaranta, M.[Mikko], Yu, X.W.[Xiao-Wei], Holopainen, M.[Markus], Hyyppä, J.[Juha],
Diameter distribution estimation with laser scanning based multisource single tree inventory,
PandRS(108), No. 1, 2015, pp. 161-171.
Elsevier DOI 1511
Remote sensing BibRef

Kankare, V.[Ville], Vastaranta, M.[Mikko], Holopainen, M.[Markus], Räty, M.[Minna], Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Hyyppä, H.[Hannu], Alho, P.[Petteri], Viitala, R.[Risto],
Retrieval of Forest Aboveground Biomass and Stem Volume with Airborne Scanning LiDAR,
RS(5), No. 5, 2013, pp. 2257-2274.
DOI Link 1307

Dalponte, M., Bruzzone, L., Gianelle, D.,
A System for the Estimation of Single-Tree Stem Diameter and Volume Using Multireturn LIDAR Data,
GeoRS(49), No. 7, July 2011, pp. 2479-2490.

See also Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas. BibRef

Lo, C.S., Lin, C.,
Growth-Competition-Based Stem Diameter and Volume Modeling for Tree-Level Forest Inventory Using Airborne LiDAR Data,
GeoRS(51), No. 4, April 2013, pp. 2216-2226.

You, L.[Lei], Tang, S.Z.[Shou-Zheng], Song, X.Y.[Xin-Yu], Lei, Y.C.[Yuan-Cai], Zang, H.[Hao], Lou, M.H.[Ming-Hua], Zhuang, C.Y.[Chong-Yang],
Precise Measurement of Stem Diameter by Simulating the Path of Diameter Tape from Terrestrial Laser Scanning Data,
RS(8), No. 9, 2016, pp. 717.
DOI Link 1610

Oveland, I.[Ivar], Hauglin, M.[Marius], Gobakken, T.[Terje], Næsset, E.[Erik], Maalen-Johansen, I.[Ivar],
Automatic Estimation of Tree Position and Stem Diameter Using a Moving Terrestrial Laser Scanner,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705

Fang, R.[Rong], Strimbu, B.M.[Bogdan M.],
Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708

Wieser, M.[Martin], Mandlburger, G.[Gottfried], Hollaus, M.[Markus], Otepka, J.[Johannes], Glira, P.[Philipp], Pfeifer, N.[Norbert],
A Case Study of UAS Borne Laser Scanning for Measurement of Tree Stem Diameter,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712

Heinzel, J.[Johannes], Huber, M.O.[Markus O.],
Tree Stem Diameter Estimation From Volumetric TLS Image Data,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706

Heinzel, J.[Johannes], Huber, M.O.[Markus O.],
Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
TLS Field Data Based Intensity Correction For Forest Environments,
ISPRS16(B8: 643-649).
DOI Link 1610

Forsman, M.[Mona], Börlin, N.[Niclas], Olofsson, K.[Kenneth], Reese, H.[Heather], Holmgren, J.[Johan],
Bias of cylinder diameter estimation from ground-based laser scanners with different beam widths: A simulation study,
PandRS(135), No. Supplement C, 2018, pp. 84-92.
Elsevier DOI 1712
Mobile laser scanning, Diameter estimation, Cylinder measurement, Simulation, Terrestrial laser scanning, Tree stem diameter BibRef

Mokroš, M.[Martin], Liang, X.[Xinlian], Surový, P.[Peter], Valent, P.[Peter], Cernava, J.[Juraj], Chudý, F.[František], Tunák, D.[Daniel], Salon, Š.[Šimon], Merganic, J.[Ján],
Evaluation of Close-Range Photogrammetry Image Collection Methods for Estimating Tree Diameters,
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804

Liu, C.[Chang], Xing, Y.Q.[Yan-Qiu], Duanmu, J.[Jialong], Tian, X.[Xin],
Evaluating Different Methods for Estimating Diameter at Breast Height from Terrestrial Laser Scanning,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805

Fan, Y.X.[Yong-Xiang], Feng, Z.K.[Zhong-Ke], Mannan, A.[Abdul], Khan, T.U.[Tauheed Ullah], Shen, C.Y.[Chao-Yong], Saeed, S.[Sajjad],
Estimating Tree Position, Diameter at Breast Height, and Tree Height in Real-Time Using a Mobile Phone with RGB-D SLAM,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Iizuka, K.[Kotaro], Yonehara, T.[Taichiro], Itoh, M.[Masayuki], Kosugi, Y.[Yoshiko],
Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802

Lin, Y.[Yi], Jiang, M.[Miao],
A New Algorithm for MLS-Based DBH Mensuration and Its Preliminary Validation in an Urban Boreal Forest: Aiming at One Cornerstone of Allometry-Based Forest Biometrics,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806

Cernava, J.[Juraj], Mokroš, M.[Martin], Tucek, J.[Ján], Antal, M.[Michal], Slatkovská, Z.[Zuzana],
Processing Chain for Estimation of Tree Diameter from GNSS-IMU-Based Mobile Laser Scanning Data,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903

Wang, P.[Pei], Gan, X.Z.[Xiao-Zheng], Zhang, Q.[Qing], Bu, G.C.[Guo-Chao], Li, L.[Li], Xu, X.X.[Xiu-Xian], Li, Y.X.[Ya-Xin], Liu, Z.C.[Zi-Chu], Xiao, X.M.[Xiang-Ming],
Analysis of Parameters for the Accurate and Fast Estimation of Tree Diameter at Breast Height Based on Simulated Point Cloud,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911

Cosenza, D.N.[Diogo Nepomuceno], Soares, P.[Paula], Guerra-Hernández, J.[Juan], Pereira, L.[Luísa], González-Ferreiro, E.[Eduardo], Castedo-Dorado, F.[Fernando], Tomé, M.[Margarida],
Comparing Johnson's SB and Weibull Functions to Model the Diameter Distribution of Forest Plantations through ALS Data,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912

Holmgren, J.[Johan], Tulldahl, M.[Michael], Nordlöf, J.[Jonas], Willén, E.[Erik], Olsson, H.[Håkan],
Mobile Laser Scanning for Estimating Tree Stem Diameter Using Segmentation and Tree Spine Calibration,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912

Corte, A.P.D.[Ana Paula Dalla], Rex, F.E.[Franciel Eduardo], de Almeida, D.R.A.[Danilo Roberti Alves], Sanquetta, C.R.[Carlos Roberto], Silva, C.A.[Carlos A.], Moura, M.M.[Marks M.], Wilkinson, B.[Ben], Zambrano, A.M.A.[Angelica Maria Almeyda], da Cunha Neto, E.M.[Ernandes M.], Veras, H.F.P.[Hudson F. P.], de Moraes, A.[Anibal], Klauberg, C.[Carine], Mohan, M.[Midhun], Cardil, A.[Adrián], Broadbent, E.N.[Eben North],
Measuring Individual Tree Diameter and Height Using GatorEye High-Density UAV-Lidar in an Integrated Crop-Livestock-Forest System,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003

Duanmu, J.L.[Jia-Long], Xing, Y.Q.[Yan-Qiu],
Annular Neighboring Points Distribution Analysis: A Novel PLS Stem Point Cloud Preprocessing Algorithm for DBH Estimation,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
PLS: Personal laser scanning. DBH: diameter of breast height. BibRef

Ye, W.F.[Wen-Fang], Qian, C.[Chuang], Tang, J.[Jian], Liu, H.[Hui], Fan, X.Y.[Xiao-Yun], Liang, X.L.[Xin-Lian], Zhang, H.J.[Hong-Juan],
Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002

Fan, Y.X.[Yong-Xiang], Feng, Z.K.[Zhong-Ke], Shen, C.Y.[Chao-Yong], Khan, T.U.[Tauheed Ullah], Mannan, A.[Abdul], Gao, X.[Xiang], Chen, P.[Panpan], Saeed, S.[Sajjad],
A trunk-based SLAM backend for smartphones with online SLAM in large-scale forest inventories,
PandRS(162), 2020, pp. 41-49.
Elsevier DOI 2004
Forest inventory, Online SLAM, Smartphone, Augmented reality, Tree position, SLAM backend, Loop closure detection, Graph optimization BibRef

Fu, L.Y.[Li-Yong], Duan, G.S.[Guang-Shuang], Ye, Q.L.[Qiao-Lin], Meng, X.[Xiang], Luo, P.[Peng], Sharma, R.P.[Ram P.], Sun, H.[Hua], Wang, G.X.[Guang-Xing], Liu, Q.W.[Qing-Wang],
Prediction of Individual Tree Diameter Using a Nonlinear Mixed-Effects Modeling Approach and Airborne LiDAR Data,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004

Yang, Z.H.[Zhao-Hui], Liu, Q.W.[Qing-Wang], Luo, P.[Peng], Ye, Q.L.[Qiao-Lin], Duan, G.S.[Guang-Shuang], Sharma, R.P.[Ram P.], Zhang, H.R.[Hui-Ru], Wang, G.X.[Guang-Xing], Fu, L.[Liyong],
Prediction of Individual Tree Diameter and Height to Crown Base Using Nonlinear Simultaneous Regression and Airborne LiDAR Data,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007

Krisanski, S.[Sean], Taskhiri, M.S.[Mohammad Sadegh], Turner, P.[Paul],
Enhancing Methods for Under-Canopy Unmanned Aircraft System Based Photogrammetry in Complex Forests for Tree Diameter Measurement,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006

Bruggisser, M.[Moritz], Hollaus, M.[Markus], Otepka, J.[Johannes], Pfeifer, N.[Norbert],
Influence of ULS acquisition characteristics on tree stem parameter estimation,
PandRS(168), 2020, pp. 28-40.
Elsevier DOI 2009
Unmanned aerial vehicle, DBH, Stem diameter, Stem reconstruction, Forest inventory, Point cloud quality BibRef

Koren, M.[Milan], Huncaga, M.[Milan], Chudá, J.[Juliana], Mokroš, M.[Martin], Surový, P.[Peter],
The Influence of Cross-Section Thickness on Diameter at Breast Height Estimation from Point Cloud,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009

Hao, Y.S.[Yuan-Shuo], Widagdo, F.R.A.[Faris Rafi Almay], Liu, X.[Xin], Quan, Y.[Ying], Dong, L.[Lihu], Li, F.R.[Feng-Ri],
Individual Tree Diameter Estimation in Small-Scale Forest Inventory Using UAV Laser Scanning,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101

Taubert, F.[Franziska], Fischer, R.[Rico], Knapp, N.[Nikolai], Huth, A.[Andreas],
Deriving Tree Size Distributions of Tropical Forests from Lidar,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101

You, L.[Lei], Wei, J.[Jie], Liang, X.J.[Xiao-Jun], Lou, M.H.[Ming-Hua], Pang, Y.[Yong], Song, X.Y.[Xin-Yu],
Comparison of Numerical Calculation Methods for Stem Diameter Retrieval Using Terrestrial Laser Data,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105

Masuda, H.[Hiroshi], Hiraoka, Y.[Yuichiro], Saito, K.[Kazuto], Eto, S.[Shinsuke], Matsushita, M.[Michinari], Takahashi, M.[Makoto],
Efficient Calculation Method for Tree Stem Traits from Large-Scale Point Clouds of Forest Stands,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107

Chisholm, R.A.[Ryan A.], Rodríguez-Ronderos, M.E.[M. Elizabeth], Lin, F.[Feng],
Estimating Tree Diameters from an Autonomous Below-Canopy UAV with Mounted LiDAR,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107

Hershey, J.L.[Jeff L.], McDill, M.E.[Marc E.], Miller, D.A.[Douglas A.], Holderman, B.[Brennan], Michael, J.H.[Judd H.],
A Voxel-Based Individual Tree Stem Detection Method Using Airborne LiDAR in Mature Northeastern U.S. Forests,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202

Sun, Y.S.[Yu-Sen], Jin, X.J.[Xing-Ji], Pukkala, T.[Timo], Li, F.R.[Feng-Ri],
Predicting Individual Tree Diameter of Larch (Larix olgensis) from UAV-LiDAR Data Using Six Different Algorithms,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203

Leclère, L.[Louise], Lejeune, P.[Philippe], Bolyn, C.[Corentin], Latte, N.[Nicolas],
Estimating Species-Specific Stem Size Distributions of Uneven-Aged Mixed Deciduous Forests Using ALS Data and Neural Networks,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204

Witzmann, S.[Sarah], Matitz, L.[Laura], Gollob, C.[Christoph], Ritter, T.[Tim], Kraßnitzer, R.[Ralf], Tockner, A.[Andreas], Stampfer, K.[Karl], Nothdurft, A.[Arne],
Accuracy and Precision of Stem Cross-Section Modeling in 3D Point Clouds from TLS and Caliper Measurements for Basal Area Estimation,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205

Kelley, J.[Jason], Trofymow, J.A.T.[J. A. Tony], Bone, C.[Christopher],
Combining Area-Based and Individual Tree Metrics for Improving Merchantable and Non-Merchantable Wood Volume Estimates in Coastal Douglas-Fir Forests,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Gao, Q.[Qiang], Kan, J.M.[Jiang-Ming],
Automatic Forest DBH Measurement Based on Structure from Motion Photogrammetry,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
Diameter at Breast Height. BibRef

Corrao, M.V.[Mark V.], Sparks, A.M.[Aaron M.], Smith, A.M.S.[Alistair M. S.],
A Conventional Cruise and Felled-Tree Validation of Individual Tree Diameter, Height and Volume Derived from Airborne Laser Scanning Data of a Loblolly Pine (P. taeda) Stand in Eastern Texas,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206

Feng, B.[Baokun], Nie, S.[Sheng], Wang, C.[Cheng], Xi, X.H.[Xiao-Huan], Wang, J.[Jinliang], Zhou, G.Q.[Guo-Qing], Wang, H.Y.[Hao-Yu],
Exploring the Potential of UAV LiDAR Data for Trunk Point Extraction and Direct DBH Measurement,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206

Machado, M.V., Tommaselli, A.M.G., Tachibana, V.M., Martins-Neto, R.P., Campos, M.B.,
Evaluation of Multiple Linear Regression Model to Obtain Dbh of Trees Using Data From a Lightweight Laser Scanning System On-board a Uav,
DOI Link 1912

Ibanez, C.A.G., Carcellar, III, B.G., Paringit, E.C., Argamosa, R.J.L., Faelga, R.A.G., Posilero, M.A.V., Zaragosa, G.P., Dimayacyac, N.A.,
Estimating DBH of Trees Employing Multiple Linear Regression Of The Best Lidar-derived Parameter Combination Automated In Python In A Natural Broadleaf Forest In The Philippines,
ISPRS16(B8: 657-662).
DOI Link 1610

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Extraction, Forest Analysis .

Last update:Aug 14, 2022 at 21:20:19